Dependent double-observer method reduces false-positive errors in auditory avian survey data.

Area of Science:

• Ecology
• Wildlife Biology
• Conservation Science

Background:

• Detection errors, including false positives, can significantly bias wildlife abundance and occupancy estimates.
• While methods exist to address false negatives (missed detections), false positives (misidentifications or double counts) are often overlooked in ecological studies.
• The dependent double-observer method is proposed to reduce false positives, but empirical evidence is lacking.

Purpose of the Study:

• To empirically test if the dependent double-observer survey method reduces false-positive rates compared to single-observer methods.
• To evaluate the performance of both naive and expert observers using these two survey methods.
• To assess the occurrence of misidentification errors across different survey scenarios and observer expertise.

Main Methods:

• Prairie songbirds were used as a model system.
• Auditory simulations of ten species' vocalizations were created.
• Naive and expert observers surveyed these simulations using both single-observer and dependent double-observer methods.

Main Results:

• The dependent double-observer method significantly lowered false-positive rates for both naive and expert observers.
• Expert observers achieved lower false-positive rates (3.2%) with the dependent double-observer method compared to single-observer surveys (9.5%).
• Naive observers also showed reduced false-positive rates (39.1%) with the dependent double-observer method versus single-observer surveys (49.1%).

Conclusions:

• The dependent double-observer survey method is effective in reducing false-positive errors in wildlife surveys.
• Expert observers demonstrate superior performance, especially when employing the dependent double-observer method.
• This study highlights the prevalence of false positives and advocates for the adoption of methods to mitigate them for more reliable ecological data.